Development of T cell receptor repertoires during childhood in health and disease

By Emma A., Bunia A., Othilia FS., Tobias C. & Joanna R.

Group 21

Introduction

Data Description

Materials: What data did you use and where did you get it from? Methods: Which modelling did you use? Think of the methods section as a recipe for how to go from raw to results => Flow chart? Discuss how data was collected or generated for your study. Include any relevant details or procedures.

Data Wrangling

<<<<<<< HEAD

Original data

# A tibble: 359 × 12
   sample_name total_templates productive_templates fraction_productive
   <chr>                 <dbl>                <dbl>               <dbl>
 1 310183_TCRB          224872               183692               0.817
 2 310110_TCRB           89218                67780               0.760
 3 310206_TCRB          114016                94082               0.825
 4 310288_TCRB          182141               148123               0.813
 5 310271_TCRB          132340               106177               0.802
 6 310244_TCRB          218280               178995               0.82 
 7 310137_TCRB          156845               130526               0.832
 8 310258_TCRB           88479                71110               0.804
 9 310127_TCRB          145463               117291               0.806
10 310300_TCRB          131632               107604               0.818
# ℹ 349 more rows
# ℹ 8 more variables: total_rearrangements <dbl>,
#   productive_rearrangements <dbl>, productive_simpson_clonality <dbl>,
#   max_productive_frequency <dbl>, locus <chr>, sample_tags <chr>, sku <chr>,
#   test_name <chr>

Augmented data

# A tibble: 13,824 × 24
   sample_name total_templates productive_templates fraction_productive
   <chr>                 <dbl>                <dbl>               <dbl>
 1 310102_TCRB          121173                96410               0.796
 2 310102_TCRB          121173                96410               0.796
 3 310102_TCRB          121173                96410               0.796
 4 310102_TCRB          121173                96410               0.796
 5 310102_TCRB          121173                96410               0.796
 6 310102_TCRB          121173                96410               0.796
 7 310102_TCRB          121173                96410               0.796
 8 310102_TCRB          121173                96410               0.796
 9 310102_TCRB          121173                96410               0.796
10 310102_TCRB          121173                96410               0.796
# ℹ 13,814 more rows
# ℹ 20 more variables: total_rearrangements <dbl>,
#   productive_rearrangements <dbl>, productive_simpson_clonality <dbl>,
#   max_productive_frequency <dbl>, locus <chr>, sku <chr>, test_name <chr>,
#   case_control <chr>, id <dbl>, timepoint <dbl>, gender <chr>,
#   ethnicity <chr>, race <chr>, age <dbl>, age_diagnosis <dbl>,
#   age_visit <dbl>, antibody <chr>, expression <dbl>, allele <chr>, …
======= 
# A tibble: 6 × 2
  sample_name sample_tags                                                       
  <chr>       <chr>                                                             
1 310183_TCRB 06 Years, 6 Years at visit, Caucasian, Control, Control 022, GAD6…
2 310110_TCRB 0 Years at visit, 09 Months, 6.37808219178082 Years at diagnosis,…
3 310206_TCRB 0 Years at visit, 10 Months, 10.558904109589 Years at diagnosis, …
4 310288_TCRB 09 Years, 9 Years at visit, 9.56986301369863 Years at diagnosis, …
5 310271_TCRB 02 Years, 2 Years at visit, 6.87397260273973 Years at diagnosis, …
6 310244_TCRB 05 Years, 18.0438356164384 Years at diagnosis, 5 Years at visit, …
>>>>>>> 5e07d0beedcc9d6012b399969affd60dc9d32a55

Right column

Antibody Expression

Antibody Expression, PCA

HLA Expression

<<<<<<< HEAD
=======
>>>>>>> 5e07d0beedcc9d6012b399969affd60dc9d32a55

HLA Expression, PCA

Discussion

Discuss the implications of your findings. Interpret the results and relate them to your objectives.

<<<<<<< HEAD - ZnT8 for control patients … - Missing values for control patients - Missing data for control makes it difficult to determine significant differences between antibody expression for case and control - Results from PCA seems to suggest reducing dimensionality of data by clustering antibodies - No dimensionality reduction suggested from PCA on HLA

Conclusion

Summarize the main points discussed in the presentation. Emphasize the significance of your work and any future directions.

  • Something …
  • Something else … THANK YOU for listening!